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The development of an evidence-based street food vending model within a socioecological framework: A guide for African countries.

Jillian HillZandile June-Rose MchizaThandi PuoaneNelia P Steyn
Published in: PloS one (2019)
In the present global economic crisis and continued rapid urbanization, street food (SF) vending has grown into a practical source of income for people in the developing world. SF are not only appreciated for their unique flavours, convenience, and affordability they also contribute to the economy of the country, the perseverance of cultural and social heritage of society, as well as the potential for maintaining and improving the nutritional status of populations. This study aimed to develop a street food vending model (SFVM) that encompasses healthy and safe food options for consumers including hygiene and safety guidelines and viable business and operations for vendors. An evidence-based approach, i.e. "systematically collected proof", was used to inform the development of this model. Phase 1 included two surveys, one of street food vendors (N = 831) and the other of consumers (N = 1047). These surveys obtained data regarding the vendors' operations and food items they sold and the consumers' purchases and their nutrition knowledge. In Phase 2, interviews and focus groups were conducted with government officials. Additionally, regulations and policies regarding street vending were reviewed to determine available regulations and policies for street food vending. In Phase 3, data from the two phases were integrated and participatory action methods involving street food vendors used to validate the findings and inform the development of a SFVM by engaging in focus group discussions with street food vendors (N = 28). The components of the proposed SFVM comprised four parts, namely a food and nutrition component, a hygiene component, a business component and a vending cart. These components serve as a guide and considers various elements of the socioecological framework, namely intrapersonal/individual and interpersonal factors, the physical environment/community as well as the policy environment. The development of this model can serve as an example to countries which have large street food vending components and wish to optimize their value by making them safe and healthy for consumers. Thus, allowing vendors to trade under optimal conditions giving due consideration to regulations and policy.
Keyphrases
  • human health
  • public health
  • healthcare
  • mental health
  • physical activity
  • risk assessment
  • cross sectional
  • machine learning
  • artificial intelligence